The annual cost of corrosion to the US economy was estimated to be $276 billion in 2002. In many cases, industry manages corrosion based on predetermined schedules using past experience as a guide. Schedule based maintenance processes are expensive because inspections or maintenance needs to be very frequent to control risk adequately, and upset events or changing environmental conditions that cause corrosion are difficult to account for using schedule based processes. Visual observation of damage is the most widely used inspection practice for identifying corrosion, and this is ineffective in inaccessible areas and costly when disassembly is required. More sophisticated nondestructive evaluation (NDE) methods are useful for detecting the resulting damage to structures caused by corrosion. Once damage is detected, significant repair costs may be incurred to restore the structure or equipment. There are substantial societal benefits, economic, health, and safety related, to be gained by moving from schedule based processes to condition based practices for corrosion control in the fields of transportation, infrastructure, and manufacturing. The goal of achieving condition based maintenance for corrosion requires monitoring technologies that can measure environmental processes and corrosion to quantify severity. This corrosion monitoring system would allow for the anticipation of damage and the performance of inspection and maintenance based on actual corrosion severity.
Corrosion monitoring technologies for asset management depend on the availability of sensing elements and reliable models for characterizing corrosion. Known sensors directly measure corrosion damage to a structure, measure environmental conditions that cause corrosion, or measure corrosion to surrogate elements that can be used to make inferences about damage state.
A first category of sensors for direct corrosion damage measurements requires intimate contact with the structure. These sensors can be difficult to install and can become a point of failure at installation points. The sensors are usually point measurements or concentrated on a single component assembly, and this increases uncertainty about processes that occur in other adjacent components. Finally, these direct measurements only detect damage to the structure under test, and sometimes this damage may require significant repair when detected. There is a need to utilize sensors and corrosion characterization methods that are easy to install, have minimal risk of becoming points of damage initiation, have wider area coverage, and can detect corrosion or conditions that cause corrosion before substantial damage has occurred.
Known environmental sensors may be used to characterize corrosive environments and parameters including pollutant levels, rainfall totals, relative humidity, and temperature. Such characterizations may produce statistically significant results, but with usually weak correlation to the actual corrosion of structures in such an environment. Although these macro-scale atmospheric data can be applied using environmental models to predict the corrosion of structures and equipment at specific geographic locations, that prediction does not capture what are often the dominant local microclimate conditions around and within a structure that control corrosion affecting that structure. The use of environmental sensors near and within a structure can overcome some of these issues, but environmental models that use parameters, such as distance to the sea or total inches of rainfall, are typically not helpful for mobile structures or interior spaces of structures.
Another category of sensors that may be used to characterize corrosion for structure monitoring and management are surrogate sensing elements that react to environmental conditions. These surrogate corrosion sensors are used to make inferences about corrosion damage to the structure of interest. Surrogate corrosion sensors can be grouped as cumulative damage sensors and corrosion rate sensors. Cumulative damage sensors are based on electrical resistance (ER) measurements, where the resistance increases with the progression of corrosion. The sensitivity of ER sensors increases as the sensing element becomes thinner, but this significantly reduces sensor lifetime. Although an ER sensor may be designed to optimize both sensitivity to corrosion and sensor lifetime, high corrosion in a local area can still substantially reduce the ER sensor's longevity. Corrosion rate sensors are used to estimate the instantaneous rate of corrosion at any given time. These sensors may be used to detect galvanic currents or free corrosion rates of metals or alloys. Cumulative corrosion damage can be estimated with these sensors by integrating the periodic corrosion rate measurements over a given time period. The total corrosion, (corresponding to a total charge passed between the sensor electrodes), for a given period of time can be converted to a material mass loss using Faraday's Law. A history of the corrosion rate data is used to estimate cumulative corrosion damage. Both the cumulative corrosion and corrosion rate sensors measure the influence of localized microenvironment conditions, and as a result, sensor placement is key to producing an accurate measure for a given structure. Placement may be associated with importance of the structural elements or based on knowledge of conditions that produce the most significant corrosion risk.
Existing sensing technology and modeling approaches are inadequate to enable condition based maintenance for corrosion damage of high value assets. The inventor recognized there is a need for environmental sensors that can be easily located within or near a structure to produce data for a corrosion classification model that is based on relevant and accessible sensor data. There is also a need to combine the strengths of individual environmental and corrosion sensing methods in a multi-faceted sensor system that can leverage both environmental and corrosion sensors for atmospheric corrosivity classification to achieve reliable corrosion damage prediction of equipment and structures in various environments, e.g., different microclimates.